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Background <p>Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofrequency ablation remains limited by a substantial rate of recurrence. The selection of anesthesia, the surgeon's operative experience and medical expertise, as well as the ablation surgery strategy, all have an impact on the recurrence after atrial fibrillation surgery. Our research aims to explore a novel method for predicting atrial fibrillation (AF) recurrence.</p> Methods <p>This study enrolled 148 patients with atrial fibrillation (AF) undergoing first-time radiofrequency ablation. Based on the data from the AIFV system (an artificial intelligence-based ablation quality analysis system that generates structured Vistag scores from CARTO3 mapping data), patients were divided into two groups: the high-score group(Vistag analysis scores ≥ V5) and the low-score group(scores &lt; V5). Baseline characteristics, intraoperative parameters, and AIFV system-related data were collected. Multivariate logistic regression analysis was performed to identify factors associated with atrial fibrillation (AF) recurrence.</p> Results <p>Among the 148 enrolled patients, 84 were categorized into the high-score group and 64 into the low-score group. Patients in the low-score group had significantly higher Left Ventricular End-Diastolic Volume (LVEDV), Left Ventricular Ejection Fraction (LVEF), and Left Ventricular End-Systolic Volume (LVESV), as well as a higher prevalence of diabetes (29.5% vs. 9.5%, <i>p =</i> 0.002). During a minimum follow-up of 365&#xa0;days, 11 patients (13.1%) in the high-score group experienced recurrence of atrial arrhythmia, compared to 19 patients (29.7%) in the low-score group. Kaplan–Meier analysis revealed a significantly higher atrial arrhythmia-free survival rate in the high-score group (log-rank test, <i>P =</i> 0.012). Multivariate logistic regression analysis revealed that being in the high-score group was an independent protective factor against AF recurrence (OR = 0.383, 95% CI 0.160–0.912, <i>P =</i> 0.030).</p> Conclusions <p>The AIFV system was used to evaluate six procedural parameters in each atrial fibrillation procedure, which could play a crucial role in predicting the recurrence of atrial fibrillation.</p>

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Predicting atrial fibrillation recurrence after radiofrequency ablation using the AIFV system: a prospective observational study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Yingrong Xin,
  • Jingchao Li,
  • Huihui Song,
  • Luqian Cui,
  • Haijia Yu,
  • Yingjie Chu,
  • Shujuan Dong

摘要

Background

Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofrequency ablation remains limited by a substantial rate of recurrence. The selection of anesthesia, the surgeon's operative experience and medical expertise, as well as the ablation surgery strategy, all have an impact on the recurrence after atrial fibrillation surgery. Our research aims to explore a novel method for predicting atrial fibrillation (AF) recurrence.

Methods

This study enrolled 148 patients with atrial fibrillation (AF) undergoing first-time radiofrequency ablation. Based on the data from the AIFV system (an artificial intelligence-based ablation quality analysis system that generates structured Vistag scores from CARTO3 mapping data), patients were divided into two groups: the high-score group(Vistag analysis scores ≥ V5) and the low-score group(scores < V5). Baseline characteristics, intraoperative parameters, and AIFV system-related data were collected. Multivariate logistic regression analysis was performed to identify factors associated with atrial fibrillation (AF) recurrence.

Results

Among the 148 enrolled patients, 84 were categorized into the high-score group and 64 into the low-score group. Patients in the low-score group had significantly higher Left Ventricular End-Diastolic Volume (LVEDV), Left Ventricular Ejection Fraction (LVEF), and Left Ventricular End-Systolic Volume (LVESV), as well as a higher prevalence of diabetes (29.5% vs. 9.5%, p = 0.002). During a minimum follow-up of 365 days, 11 patients (13.1%) in the high-score group experienced recurrence of atrial arrhythmia, compared to 19 patients (29.7%) in the low-score group. Kaplan–Meier analysis revealed a significantly higher atrial arrhythmia-free survival rate in the high-score group (log-rank test, P = 0.012). Multivariate logistic regression analysis revealed that being in the high-score group was an independent protective factor against AF recurrence (OR = 0.383, 95% CI 0.160–0.912, P = 0.030).

Conclusions

The AIFV system was used to evaluate six procedural parameters in each atrial fibrillation procedure, which could play a crucial role in predicting the recurrence of atrial fibrillation.